feat: add prompt startup actions and shared vision config
This commit is contained in:
Xin Wang
@@ -5,9 +5,7 @@ from __future__ import annotations
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import asyncio
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from copy import deepcopy
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from dataclasses import replace
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from time import monotonic
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from typing import Any
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from uuid import uuid4
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from loguru import logger
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from models import AssistantConfig, RuntimeTool
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@@ -36,19 +34,18 @@ from services.brains.base import (
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BrainSpec,
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SessionVariableUpdate,
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)
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from services.action_runtime import (
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ActionInvocationCancelled,
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ActionOutcome,
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ActionRunner,
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ActionStatus,
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)
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from services.knowledge import search as search_knowledge
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from services.runtime_variables import DynamicVariableStore
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from services.tool_executor import ToolExecutionError, ToolExecutor
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from services.tool_policy import policy_for_tool
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from services.workflow.agent import WorkflowAgentStage
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from services.workflow.models import (
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ActionError,
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ActionOutcome,
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ActionStatus,
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RouteStatus,
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WorkflowRuntimeState,
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WorkflowStatus,
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)
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from services.workflow.models import RouteStatus, WorkflowRuntimeState, WorkflowStatus
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from services.workflow.output import WorkflowOutput
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from services.workflow.routing import WorkflowEdgeEvaluator
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from services.workflow_engine import WorkflowEngine
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@@ -58,23 +55,6 @@ from services.workflow_router import WorkflowLLMRouter
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MAX_AUTOMATIC_HOPS = 50
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class _ActionFailure(RuntimeError):
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"""Internal adapter from heterogeneous tool failures to ActionOutcome."""
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def __init__(
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self,
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message: str,
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*,
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code: str,
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retryable: bool = False,
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result: dict[str, Any] | None = None,
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) -> None:
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super().__init__(message)
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self.code = code
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self.retryable = retryable
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self.result = result
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class ConfiguredFlowManager(FlowManager):
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"""Preserve Flow transitions while suppressing late async-tool replies."""
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@@ -129,6 +109,7 @@ class WorkflowBrain(BaseBrain):
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self._cfg = cfg
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self._store = DynamicVariableStore.from_config(cfg or AssistantConfig(type="workflow"))
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self._tools = ToolExecutor(self._store)
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self._actions = ActionRunner(self._tools)
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self._tool_by_id: dict[str, RuntimeTool] = {
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tool.id: tool for tool in (cfg.tools if cfg else [])
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}
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@@ -166,6 +147,10 @@ class WorkflowBrain(BaseBrain):
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self._runtime = runtime
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self._store = DynamicVariableStore.from_config(cfg)
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self._tools = ToolExecutor(self._store, client_tools=runtime.client_tools)
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self._actions = ActionRunner(
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self._tools,
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is_session_ending=lambda: runtime.call_end.ending,
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)
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self._tool_by_id = {tool.id: tool for tool in cfg.tools}
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self._router = WorkflowLLMRouter(cfg)
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self._edge_evaluator = WorkflowEdgeEvaluator(
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@@ -749,8 +734,7 @@ class WorkflowBrain(BaseBrain):
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await self._emit_node_active(node_id)
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data = self._engine.data(node_id)
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runtime = self._require_runtime()
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invocation_id = f"act_{uuid4().hex[:20]}"
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started_at = monotonic()
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invocation_id = self._actions.new_invocation_id()
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block_user_input = data.get("userInputPolicy") == "block"
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if block_user_input and runtime.set_input_enabled:
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# Blocking only suppresses new audio/text input while the Action
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@@ -760,7 +744,6 @@ class WorkflowBrain(BaseBrain):
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runtime.set_input_enabled(False)
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tool_id = str(data.get("toolId") or "")
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tool = self._tool_by_id.get(tool_id)
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result: dict[str, Any] | None = None
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try:
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await self._emit_trace(
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"action_started",
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@@ -769,82 +752,24 @@ class WorkflowBrain(BaseBrain):
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toolId=tool_id,
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toolType=tool.type if tool else None,
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)
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if not tool:
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raise _ActionFailure(
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f"工具不存在:{tool_id}",
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code="tool_not_found",
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)
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arguments = self._store.render_data(data.get("arguments") or {})
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result = await self._tools.execute(
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outcome = await self._actions.execute(
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tool,
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arguments,
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data.get("arguments") or {},
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result_assignments=self._action_result_assignments(data),
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invocation_id=invocation_id,
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)
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if result.get("status") != "ok":
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returned_status = str(result.get("status") or "error")
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raise _ActionFailure(
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str(result.get("message") or "工具返回执行失败状态"),
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code=str(result.get("code") or f"tool_{returned_status}"),
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retryable=bool(result.get("retryable", False)),
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result=result,
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)
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updated_variables = list(result.get("updated_variables") or [])
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updated_variables = list(outcome.updated_variables)
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if updated_variables:
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await self._emit_variables(
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reason="action",
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node_id=node_id,
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changed=updated_variables,
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)
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outcome = ActionOutcome(
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invocation_id=invocation_id,
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status=ActionStatus.SUCCESS,
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duration_ms=self._elapsed_ms(started_at),
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result=result,
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updated_variables=tuple(str(name) for name in updated_variables),
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)
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except asyncio.CancelledError:
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outcome = ActionOutcome(
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invocation_id=invocation_id,
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status=ActionStatus.CANCELLED,
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duration_ms=self._elapsed_ms(started_at),
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result=result,
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error=ActionError(
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code="action_cancelled",
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message="Action 随当前任务取消",
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),
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)
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except ActionInvocationCancelled as exc:
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outcome = exc.outcome
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self._set_last_action(outcome)
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await self._emit_action_outcome(node_id, outcome)
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raise
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except (_ActionFailure, ToolExecutionError, ValueError) as exc:
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cancelled = self._action_was_cancelled(exc, runtime)
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outcome = ActionOutcome(
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invocation_id=invocation_id,
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status=(
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ActionStatus.CANCELLED if cancelled else ActionStatus.FAILURE
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),
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duration_ms=self._elapsed_ms(started_at),
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result=(exc.result if isinstance(exc, _ActionFailure) else result),
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error=ActionError(
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code=(
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"session_ended"
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if cancelled
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else (
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exc.code
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if isinstance(exc, _ActionFailure)
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else (
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"invalid_action_configuration"
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if isinstance(exc, ValueError)
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else "tool_execution_error"
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)
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)
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),
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message=str(exc)[:2048],
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retryable=(
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exc.retryable if isinstance(exc, _ActionFailure) else False
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),
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),
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)
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finally:
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if block_user_input and runtime.set_input_enabled:
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runtime.set_input_enabled(True)
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@@ -852,26 +777,6 @@ class WorkflowBrain(BaseBrain):
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await self._emit_action_outcome(node_id, outcome)
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return outcome
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@staticmethod
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def _elapsed_ms(started_at: float) -> int:
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return max(0, round((monotonic() - started_at) * 1000))
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@staticmethod
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def _action_was_cancelled(exc: Exception, runtime: BrainRuntime) -> bool:
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if getattr(runtime.call_end, "ending", False):
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return True
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message = str(exc)
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return any(
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marker in message
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for marker in (
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"会话已结束",
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"会话已取消",
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"管线已停止",
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"通道已关闭",
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"连接已断开",
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)
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)
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def _set_last_action(self, outcome: ActionOutcome) -> None:
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legacy_status = {
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ActionStatus.SUCCESS: "ok",
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